Distribution systems cost reduction based on switches upgrades: A stochastic approach

摘要

? 2022 Elsevier B.V.Power Distribution Systems are considered critical infrastructures, and their continuity to deliver and maintain electricity to the final customer is of extreme importance. The Optimal Switch Allocation address this topic by changing the network configuration to improve reliability, while minimizing power loss and cost. On previous researches economic constraints and dynamic failure models were considered, but neither the uncertainty in the environmental parameters nor stochastic models are applied. Additionally, the possibility to upgrade existing switches are often not considered. This work applies a Genetic Algorithm, coupled with Monte Carlo Simulation, as well as a Bayesian Inference Model, to address the probability of upgrading existing switches in a power distribution system. Economical constraints, fragility curves, variable load demand and weather scenarios are simulated. The Bayesian inference allows the model to be used as a support decision tool, when dealing with the possibility of upgrading switches in the network, especially in face of uncertainties in the distribution system. Results show that the upgrade of existing switches can achieve total cost reduction, but the uncertainties presented in the model can change the probability of upgrading an individual switch, thus sustaining the importance of the proposed approach.